
VOC 2007 [1]}:
Pascal Visual Object Classes Challenge (VOC 2007) dataset [1]} contains 9,963 images from 20 objects (i.e., classes). On average, each image has 2.5 objects. Following previous work [3]}, we split the dataset into 5,011 training images and 4,952 testing images.


MS-COCO [4]}: Microsoft-COCO (MS-COCO) [4]} dataset contains 82,081 training images, 40,504 validation images, and 40,775 testing images from 80 objects. Each image has 2.9 objects on average. The images in the testing dataset do not have ground truth labels. Therefore, following previous work [6]}, we evaluate our method on the validation dataset.

NUS-WIDE [7]}: NUS-WIDE dataset [7]} originally contains 269,648 images from Flickr. The images are manually annotated into 81 visual concepts, with 2.4 visual concepts per image on average. Since the URLs of certain images are not accessible,
we adopt the version released by [9]}, which contains 154,000 training images and 66,000 testing images.

